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Collective Intelligence and Social Content Semantic Analysis

Collective Intelligence and Social Content Semantic Analysis. Introduction to Collective Intelligence (CI), Yiannis Kompatsiaris, ITI Semantics through CI, Steffen Staab, Univ. Koblenz Web 2.0 applications and CI, Ricardo Baeza-Yates, Yahoo Research

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Collective Intelligence and Social Content Semantic Analysis

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  1. Collective Intelligence and Social Content Semantic Analysis • Introduction to Collective Intelligence (CI), Yiannis Kompatsiaris, ITI • Semantics through CI, Steffen Staab, Univ. Koblenz • Web 2.0 applications and CI, Ricardo Baeza-Yates, Yahoo Research • Social Network Analysis and CI, Andreas Geyer-Schulz, Univ. Karlsruhe • CI through the lens of a company, Andre Skusa, Lycos Europe • User Interfaces and Interaction for CI, Vitaveska Lanfranchi, Univ. of Sheffield • Human-Centered Approaches to Data Mining: Where does Culture meet Statistics?, Alejandro Jaimes-Larrarte, Telefonica

  2. Yiannis Kompatsiaris CERTH – ITI Multimedia Knowledge Laboratory An IntroductionToCollective Intelligence

  3. Defining Collective Intelligence “Collective Intelligence is the INTELLIGENCE of a COLLECTIVE, which arises from a number of SOURCES” ...an INTELLIGENCE that an individual cannot achieve by itself

  4. What is collective? Human Collectives (e.g. communities, groups, organizations, families)‏ Groups of intelligent agents in computer environments Animal Collectives (e.g. ants, birds, bees)‏

  5. Who is intelligent? There are too many different definitions out there. Defining intelligence is controversial and elusive activity. Characteristics, capacities, functions that can be ascribed to intelligence problem solving decision making integration, synthesis applying knowledge reasoning information gathering, sorting and categorization evolution

  6. Why today? Web 2.0 (Collective)‏ Semantics (Intelligence)‏ Mobile / Networks

  7. Collective Intelligence Overview Commenting Rating Annotating/ Tagging Co-editing Presentation Networks Processes Recommendations Access – Browsing – Retrieval User-generated content Sources of CI Consumption Conversations / Discussions Rersonalised services Analysis User feedbacks Trend detection Social connectivity Network Analysis Meaning from content Content Analysis Added-value in services Tag Analysis Statistical Analysis Collective Intelligence

  8. Analysis? What analysis? Content high co-editing/presentation link analysis/PageRank media – mass – social analysis tag analysis / personalization tag analysis medium recommendations statistic analysis/dynamics low low medium Analysis high

  9. WeKnowIt and CI Decomposition of Collective Intelligence Media Intelligence Mass Intelligence Social Intelligence Blogs, forums, ratings, voting User-generated content Social Networks SOURCES OF CI Harnessing CI COLLECTIVE/ CONSUMERS Organizational Intelligence Personal Intelligence

  10. Personal Intelligence Profile of contributor>> What to send where, e.g. location, age, picture Media Intelligence Picture arrives at emergency response>> Automatic detection of a fire event Buncefield 2005 Organizational Intelligence The right knowledge to the right people at the right time >> Whom (fire-fighters, ambulances,…) to inform about what Mass Intelligence Many contributors>> Extraction of trends about the scale of the incident Buncefield 2005 Social Intelligence Collective intelligence - the full picture emerges Trust and feedback>> Determine trustworthiness and hub-structures by SNA

  11. Issues Trust, security, privacy, wrong data Applications and commercialization Integration with services - organizations Efficiency of semantics and analysis Real integration not just sum of different analysis User interaction Performance, scalability speed, storage, power

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